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In essence, I have a data frame that looks something like this

unix time a b c d e f
timestamp something something relevant info 1 something something string 1
timestamp something something relevant info 1 something something string 2

(goes on for ~50k entries with something like 25 unique strings)

and I need to plot the relevant information in column c against the timestamps in the unix time column, making a new plot for each unique string in column f. In other words, each plot should hold only elements of the data frame that have one particular value for the string in column f. How should I go about doing this? I tried the dict approach that shows up elsewhere on this site, but I can't get matplotlib to plot a dict entry.

As a side note, is there some way to convert from unix time to ISO time before plotting?

Andrej Kesely
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Neptun0-
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    Welcome to stack overflow. It would be helpful if you would [edit] your question to include a [mcve] with some more representative sample input data and expected output , and code for what you've tried so far based on your own research. This would help us to understand how best to help you. Have a look at [How to make good pandas examples](https://stackoverflow.com/questions/20109391/how-to-make-good-reproducible-pandas-examples) – G. Anderson Mar 16 '21 at 22:29

1 Answers1

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You can use seaborn catplot() for the plotting:

https://seaborn.pydata.org/generated/seaborn.catplot.html https://seaborn.pydata.org/tutorial/categorical.html

Conversion from unix time to ISO time has been solved here: Convert unix time to readable date in pandas dataframe

Nike
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